A Comparative Study between PCA and SOM for Plastic Surgery Face Recognition

Now a day, people are using various advanced technologies to solve their real life problem, affordability and the speed with which these procedures can be performed are one of the reasons. Plastic surgery is an example of one of the advanced technologies, which is used to transform a persons physical feature or rather appearance of various facial features (some time non-face features). In this paper we will explain how plastic surgery can affect the process of face recognition [1] [2] [3] and also describe two very popular face recognition techniques, PCA (Principal Component Analysis) and SOM (Self Organizing Map) for plastic surgery face recognition. We will also compare their performance. In case of a face recognition technique, we use database of face images where we can store face images of different expression, pose for the same person. Now for a given input image with different expression and pose the above two approaches PCA (Appearance based method) and SOM (Pattern recognition based) will work properly. Whereas in case of plastic surgery face recognition, they may not give satisfactory result, but between these two techniques SOM is more better than PCA and perform more accurately.